RoBERTa-Large-Chunk [1]} is an end-to-end method without explicit evidence retrieval. This model splits the long passages into fix-length chunks of 200 tokens. Candidate answers are obtained from each chunk using existing MRC models, which are further aggregated over all chunks. We use the pre-trained Chinese RoBERTa-wwm-ext-Large [2]}.
